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| http://dx.doi.org/10.5688/ajpe7054 | DOI Listing |
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Positive affect amplifies integration within episodic memories in the laboratory and the real world.
Learn Mem
January 2025
Department of Psychiatry, Yale University, New Haven, Connecticut 06511, USA
Emotional events hold a privileged place in our memories, differing in accuracy and structure from memories for neutral experiences. Although much work has focused on the pronounced differences in memory for negative experiences, there is growing evidence that positive events may lead to more holistic, or integrated, memories. However, it is unclear whether these affect-driven changes in memory structure, which have been found in highly controlled laboratory environments, extend to real-world episodic memories.
View Article and Find Full Text PDFReal-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition.
Sensors (Basel)
January 2025
Department of Artifcial Intelligence, Chung-Ang University, Heukseok-dong, Dongjak-gu, Seoul 06974, Republic of Korea.
Sensor-based gesture recognition on mobile devices is critical to human-computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduced, incurring substantial energy consumption and latency due to frequent data transmission. To address these limitations, we present the first on-device continual learning framework for gesture recognition.
View Article and Find Full Text PDFApplying MLP-Mixer and gMLP to Human Activity Recognition.
Sensors (Basel)
January 2025
Graduate School of National Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan.
The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. Recently, high-performing models based on Transformers and multi-layer perceptrons (MLPs) have also been proposed.
View Article and Find Full Text PDFReal-time mechanism-based interventions for daily alcohol challenges: Protocol for ecological momentary assessment and intervention.
Digit Health
January 2025
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.
Background: Advancing evidence-based, tailored interventions for substance use disorders (SUDs) requires understanding temporal directionality while upholding ecological validity. Previous studies identified loneliness and craving as pivotal factors associated with alcohol consumption, yet the precise directionality of these relationships remains ambiguous.
Objective: This study aims to establish a smartphone-based real-life intervention platform that integrates momentary assessment and intervention into everyday life.
Criterion validity of five open-source app-based cognitive and sensory tasks in an Australian adult life course sample aged 18 to 82: Labs without walls.
Behav Res Methods
January 2025
School of Psychology, University of New South Wales, Sydney, Australia.
With recent technical advances, many cognitive and sensory tasks have been adapted for smartphone testing. This study aimed to assess the criterion validity of a subset of self-administered, open-source app-based cognitive and sensory tasks by comparing test performance to lab-based alternatives. An in-person baseline was completed by 43 participants (aged 21 to 82) from the larger Labs without Walls project (Brady et al.
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